predictive

predictive delivery

Keyword search is outdated. It requires users to know what to ask, how to phrase it, and which keywords to use, creating friction and missed opportunities. Meanwhile, targeting on social media is becoming less effective due to rising privacy restrictions and anonymous browsing behavior. Mosaic bypasses these limitations by studying user queries and behavior across AI models to understand real intent, in real time.

Our system builds a knowledge graph about each user’s interests and goals, across models, enabling us to deliver relevant ads before they even search. Here are a few examples:

Queries across models by user: (_user_299249111-49942114042):
- ChatGPT Store: "What are the top 5 ways to make money online" = (#_chatgpt_49292442)
- Deep.ai: "Should I use affiliate links as a revenue driver?" = (#_deepai_02492413)
- Agent.ai: "Is LTK a good way to make extra money?" = (#_agentai_88243210)
- Anthropic: "What jobs are a good match for my skills?" = (#_anthropic_77237122)

Mosaic Knowledge Graph attribution for user: (_user_299249111-49942114042)
(#_chatgpt_49292442) = make money online
(#_deepai_02492413) = affiliate links
(#_agentai_88243210) = LTK
(#_anthropic_77237122) = jobs

Suggested Ad Unit for user: (_user_299249111-49942114042):
($_beehiiv_41924420)

This predictive approach makes our ads feel natural and timely, not intrusive, while circumventing cookie death and privacy laws. The result is clear: a click-through rate of nearly 3 percent for higher quality predictive advertising, significantly outperforming traditional channels. Mosaic turns AI into an intent engine—and advertisers into trusted guides.